Methods for predicting the energy value of commercial dog foods
- Autores: Marta Hervera Abad
- Directores de la Tesis: Carlos Castrillo Gonzalez (dir. tes.), María Dolores Baucells Sánchez (dir. tes.)
- Lectura: En la Universitat Autònoma de Barcelona ( España ) en 2011
- Idioma: inglés
- Tribunal Calificador de la Tesis: José Antonio Guada Vallepuga (presid.), Cecilia Villaverde (secret.), Liviana Prola (voc.)
- Materias:
- Enlaces
- Tesis en acceso abierto en: TESEO
- Resumen
The pet food market has expanded continuously over recent decades. Commercial dog food energy content may be determined by in vivo feeding trials, however feeding trials necessitates of experimental animals and is too expensive and time consuming to be used in routine. Consequently, this information is not always available for the pet owner or the pet care professionals. That is why different indirect methods have been proposed in order to estimate as reliable an accurate as possible the digestible energy content of pet foods, using variables that can be analysed easily at a reasonable low cost and with a good reproducibility. This work analyses the main approaches proposed so far to estimate the digestible energy content of foods for dogs. The former method proposed by the National Research Council estimates the digestible energy content of pet foods from proximal chemical analysis using the modified Atwater factors, assuming constant apparent digestibility coefficients for each analytical fraction. This approach ignores existing differences in the digestibility of nutrients among dietary ingredients and processing methods, resulting in inaccurate estimations of energy content given the great diversity of products on the pet-food market today. Modified Atwater factors systematically underestimate the DE content of low-fibre foods whereas overestimate those high in fibre. Recently, different equations have been proposed for dogs and cats based in the estimation of apparent digestibility of energy by the crude fibre content, which improve the accuracy of prediction. Some of these equations have been included in the new NRC edition. However, the equation proposed for dogs is not accurate when applied to high CF foods (above 8%), for which predicted ME is generally underestimated. Last studies suggest more accurate results using total dietary fibre for dry dog foods. In any case, whatever the method of analysis used, differences in energy digestibility related with food processing and fibre digestibility are unlikely to be accounted for. A simple in vitro enzymatic method is proposed based in the close relationship that exists between energy digestibility and organic matter disappearance after two consecutive enzymatic (pepsin-pancreatin) incubation of food sample. The two steps in vitro method gave better estimations of in vivo energy digestibility than methods based in chemical analysis, because takes into account availability of nutrients. Nutrient composition and energy value of pet foods can be also accurately and simultaneously predicted using near infrared reflectance spectroscopy (NIRS). The precision of using NIRS to predict the digestible energy content of compound extruded foods for dogs is similar or better than by proximate chemical analysis.
